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At least 235 records · Page 13

High Performance, Web-Based, Real-Time Telemetry Visualization for Deep Space Mission Support and Operations

The Jet Propulsion Laboratory’s Mission ControlSystems Section and Mobility and Robotic Systems Section havepartnered to developed a high-performance telemetry visualizationsystem, based on our mature, web-based, 3D visualizationsoftware technology, that provides mission trajectory designers,operations personnel and reconstruction analysts with a highlyaccurate, re-usable, multi-mission solution to interactively visualizeresults from Entry, Descent and Landing (EDL) simulations,real-time mission test beds, live telemetry streams during criticalmission events, such as landing, as well as post-event reconstructionanalysis. This work builds on previous mission visualizationsystems that we have deployed for a variety of flight missions andJPL organizations including NASA’s Mars Science Laboratory(MSL), NASA’S Low Density Supersonic Decelerator (LDSD),NASA’s Soil Moisture Active Passive (SMAP), JPL’s MoonRiseLunar sample return proposal. JPL’s mission design teams, JPL’sOffice of Naval Research tasks, and JPL’s Education and PublicOutreach Office.

Wenzel, Sean↗

JEM-EF Space Station Carrier System

The NASA/GSFC Shuttle Small Payloads Projects Office (SSPPO) is developing a carrier system for accommodating scientific and applications payloads on the Japanese Experiment Module - Exposed Facility (JEM-EF). The carrier structure provides for flexible mounting of payload instrumentation in nadir, zenith, or limb-viewing positions. Avionics capability will be provided to accommodate up to four payloads with independent power and signal connections. The JEM-EF carrier builds on over 15 years of experience in developing and operating the "Hitchhiker" carriers used on the Space Shuttle. This paper describes the carrier system, potential payload configurational and related GSFC activities.

Daelemans, Gerard J.↗

Artemis and Ethics Workshop Lessons Learned

As NASA lays out its Artemis activities, it expects to set precedents in spaceflight for decades to come. Artemis is a far more ambitious program than even Apollo, aimed at developing a sustained human presence on and around the lunar surface, in preparation for Mars exploration. As a result, considering ethical and social concerns in the discussion and design of Artemis is vital to ensuring the future worlds we create are ones where humanity collectively wants to live. By understanding how to reflect on these issues as NASA makes decisions related to Artemis, NASA can avoid unintended consequences stemming from cultural perceptions of human exploration of the solar system that may harm society. We recognize that a diverse range of groups need to be part of this conversation. There are many different views about the work that should happen in space. We recognize that NASA does not hold sole responsibility for determining the ethical path forward in space, as decisions made by commercial, international, and intergovernmental partners play a major role. Inclusive conversations help inform that work. Others have already argued that social scientists and engineers need to work together with inputs from stakeholders to design the future. To begin to answer this need, NASA’s Office of Technology, Policy, and Strategy (OTPS) hosted an Artemis and Ethics Workshop. This workshop was held in Washington, DC from April 12th-14th, 2023 and brought together invited experts in social science fields and NASA managers to discuss ethical, legal, and social aspects (ELSA) of Artemis and human exploration in general. The goal of the workshop was to discuss issues and build connections that NASA managers can consider across variety of ethical issues surrounding Artemis.

Katherine T McBrayer↗

Advancing Drought Understanding, Monitoring and Prediction

Having the capacity to monitor droughts in near-real time and providing accurate drought prediction from weeks to seasons in advance can greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. The congressional mandate to establish the National Integrated Drought Information System (NIDIS; Public Law 109-430) in 2006 was a major impulse to develop, integrate, and provide drought information to meet the challenges posed by this hazard. Significant progress has been made on many fronts. On the research front, efforts by the broad scientific community have resulted in improved understanding of North American droughts and improved monitoring and forecasting tools. We now have a better understanding of the droughts of the twentieth century including the 1930s "Dust Bowl"; we have developed a broader array of tools and datasets that enhance the official North American Drought Monitor based on different methodologies such as state-of-the-art land surface modeling (e.g., the North American Land Data Assimilation System) and remote sensing (e.g., the evaporative stress index) to better characterize the occurrence and severity of drought in its multiple manifestations. In addition, we have new tools for drought prediction [including the new National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2, for operational prediction and an experimental National Multimodel Ensemble] and have explored diverse methodologies including ensemble hydrologic prediction approaches. Broad NIDIS-inspired progress is influencing the development of a Global Drought Information System (GDIS) under the auspices of the World Climate Research Program. Despite these advances, current drought monitoring and forecasting capabilities still fall short of users' needs, especially the need for skillful and reliable drought forecasts at regional and local scales. To tackle this outstanding challenging problem, focused and coordinated research efforts are needed, drawing from excellence across the broad drought research community. To meet this challenge, National Oceanic and Atmospheric Administration (NOAA)'s Drought Task Force was established in October 2011 with the ambitious goal of achieving significant new advances in the ability to understand, monitor, and predict drought over North America. The Task Force (duration of October 2011-September 2014) is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in partnership with NIDIS. It brings together over 30 leading MAPP-funded drought scientists from multiple academic and federal institutions [involves scientists from NOAA's research laboratories and centers, the National Aeronautics and Space Administration (NASA), U.S. Department of Agriculture, National Center for Atmospheric Research (NCAR), and many universities] in a concerted research effort that builds on individual MAPP research projects. These projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those aimed at testing new drought monitoring and prediction tools for operational and service purposes (as part of NCEP's Climate Test Bed). The Drought Task Force provides focus and coordination to MAPP drought research activities and also facilitates synergies with other national and international drought research efforts, including those by the GDIS.

GDIS↗

Exploration planning in the context of human exploration and development of the Moon

It is widely believed that the next step beyond low Earth orbit in attaining the United States' stated goal of 'Expanding human presence beyond the Earth' should be to reestablish a lunar capability, building on the Apollo program, and preparing the way for eventual human missions to Mars. The Moon offers important questions in planetary and Earth science, can provide a unique platform for making astronomical observations of high resolution and sensitivity, and can be in the development path for unlocking resources of the inner solar system to support space activities and return benefits to Earth. NASA's Office of Exploration has undertaken the planning of future lunar exploration missions with the assistance of the Solar System Exploration Division in matters dealing with the quality of scientific data and the manner in which it will be made available to the scientific community. The initial elements of the proposed program include the Lunar Scout missions, which consist of two small identical spacecraft in polar orbit around the Moon, which can accomplish most of the objectives associated with previous proposals for Lunar Polar Orbiters. These missions would be followed by 'Artemis' landers, capable of emplacing up to 200 kg payloads anywhere on the Moon. In addition, the exploration program must incorporate data obtained from other missions, including the Galileo lunar flybys, the Clementine high orbital observations, and Japanese penetrator missions. In the past year, a rather detailed plan for a 'First Lunar Outpost (FLO)' which would place 4 astronauts on the lunar surface for 45 days has been developed as a possible initial step of a renewed human exploration program. In the coming year, the FLO concept will be reviewed and evolved to become more highly integrated with planning for the initial human exploration of Mars, which could come perhaps 5 years after the reestablishment of lunar capability. Both programs could benefit from the common development of systems and subsystems, where that is sensible from a performance perspective.

Duke, Michael B.↗

Activation Energy

Teaming is so common in today's project management environment that most of us assume it comes naturally. We further assume that when presented with meaningful and challenging work, project teams will naturally engage in productive activity to complete their tasks. This assumption is expressed in the simple (but false) equation: Team + Work = Teamwork. Although this equation appears simple and straightforward, it is far from true for most project organizations whose reality is a complex web of institutional norms based on individual achievement and rewards. This is illustrated by the very first successful team experience from my early Air Force career. As a young lieutenant, I was sent to Squadron Officer School, which was the first in the series of Air Force professional military education courses I was required to complete during my career. We were immediately formed into teams of twelve officers. Much of the course featured competition between these teams. As the most junior member of my team, I quickly observed the tremendous pressure to show individual leadership capability. At one point early in the course, almost everyone in our group was vying to become the team leader. This conflict was so intense that it caused us to fail miserably in our first outdoor team building exercise. We spent so much time fighting over leadership that we were unable to complete any of the events on the outdoor obstacle course. This complete lack of success was so disheartening to me that I gave our team little hope for future success. What followed was a very intense period of bickering, conflict, and even shouting matches as our dysfunctional team tried to cope with our early failures and find some way to succeed. British physician and researcher Wilfred Bion (Experiences in Groups, 1961) discovered that there are powerful psychological forces inherent in all groups that divert from accomplishing their primary tasks. To overcome these restraining forces and use the potential power of the team, greater emphasis must be placed on establishing and maintaining group cohesiveness. This relationship is expressed in the revised (true) mathematical equation: Team + Work (on the Team) = Teamwork.

Gadeken, Owen↗

Performance of a Fuel-Cell-Powered, Small Electric Airplane Assessed

Rapidly emerging fuel-cell-power technologies may be used to launch a new revolution of electric propulsion systems for light aircraft. Future small electric airplanes using fuel cell technologies hold the promise of high reliability, low maintenance, low noise, and - with the exception of water vapor - zero emissions. An analytical feasibility and performance assessment was conducted by NASA Glenn Research Center's Airbreathing Systems Analysis Office of a fuel-cell-powered, propeller-driven, small electric airplane based on a model of the MCR-01 two-place kitplane (Dyn'Aero, Darois, France). This assessment was conducted in parallel with an ongoing effort by the Advanced Technology Products Corporation and the Foundation for Advancing Science and Technology Education. Their project - partially funded by a NASA grant - is to design, build, and fly the first manned, continuously propelled, nongliding electric airplane. In our study, an analytical performance model of a proton exchange membrane (PEM) fuel cell propulsion system was developed and applied to a notional, two-place light airplane modeled after the MCR-01 kitplane. The PEM fuel cell stack was fed pure hydrogen fuel and humidified ambient air via a small automotive centrifugal supercharger. The fuel cell performance models were based on chemical reaction analyses calibrated with published data from the fledgling U.S. automotive fuel cell industry. Electric propeller motors, rated at two shaft power levels in separate assessments, were used to directly drive a two-bladed, variable-pitch propeller. Fuel sources considered were compressed hydrogen gas and cryogenic liquid hydrogen. Both of these fuel sources provided pure, contaminant-free hydrogen for the PEM cells.

Berton, Jeffrey J.↗

Can We Power Future Mars Missions?

The Vision for Space Exploration identified the exploration of Mars as one of the key pathways. In response, NASAs Mars Program Office is developing a detailed mission lineup for the next decade that would lead to future explorations. Mission architectures for the next decade include both orbiters and landers. Existing power technologies, which could include solar panels, batteries, radioisotope power systems, and in the future fission power, could support these missions. Second and third decade explorations could target human precursor and human in-situ missions, building on increasingly complex architectures. Some of these could use potential feed forward from earlier Constellation missions to the Moon, discussed in the ESAS study. From a potential Mars Sample Return mission to human missions the complexity of the architectures increases, and with it the delivered mass and power requirements also amplify. The delivered mass at Mars mostly depends on the launch vehicle, while the landed mass might be further limited by EDL technologies, including the aeroshell, parachutes, landing platform, and pinpoint landing. The resulting in-situ mass could be further divided into payload elements and suitable supporting power systems. These power systems can range from tens of watts to multi-kilowatts, influenced by mission type, mission configuration, landing location, mission duration, and season. Regardless, the power system design should match the power needs of these surface assets within a given architecture. Consequently, in this paper we will identify potential needs and bounds of delivered mass and architecture dependent power requirements to surface assets that would enable future in-situ exploration of Mars.

solar panels↗

Impact of Powder Variability on the Microstructure and Mechanical Behavior of Selective Laser Melted (SLM) Alloy 718

Nickel Alloy 718 has found wide use in high-temperature aerospace applications (up to 700°C), due to a combination of good mechanical properties, environmental resistance, and workability at moderate cost. These properties have led Alloy 718 to early adoption by selective laser melting (SLM) additive manufacturing. This presentation will share results from a comprehensive industry survey of 718 powder feedstock for SLM. The survey focuses on the impact of variability in powder characteristics on build quality, microstructure, tensile and high cycle fatigue in the as-fabricated and machined surface conditions. The investigation includes sixteen powder lots from eight suppliers that are produced by gas atomization or rotary atomization in argon or nitrogen. This research was previously presented and published at the 9th International Symposium on Superalloy 718 & Derivatives and was funded by NASA Space Launch System Liquid Engine Office with the Human Exploration Operations Mission Directorate.

Sudbrack, Chantal↗

Development of a funding, cost, and spending model for satellite projects

The need for a predictive budget/funging model is obvious. The current models used by the Resource Analysis Office (RAO) are used to predict the total costs of satellite projects. An effort to extend the modeling capabilities from total budget analysis to total budget and budget outlays over time analysis was conducted. A statistical based and data driven methodology was used to derive and develop the model. Th budget data for the last 18 GSFC-sponsored satellite projects were analyzed and used to build a funding model which would describe the historical spending patterns. This raw data consisted of dollars spent in that specific year and their 1989 dollar equivalent. This data was converted to the standard format used by the RAO group and placed in a database. A simple statistical analysis was performed to calculate the gross statistics associated with project length and project cost ant the conditional statistics on project length and project cost. The modeling approach used is derived form the theory of embedded statistics which states that properly analyzed data will produce the underlying generating function. The process of funding large scale projects over extended periods of time is described by Life Cycle Cost Models (LCCM). The data was analyzed to find a model in the generic form of a LCCM. The model developed is based on a Weibull function whose parameters are found by both nonlinear optimization and nonlinear regression. In order to use this model it is necessary to transform the problem from a dollar/time space to a percentage of total budget/time space. This transformation is equivalent to moving to a probability space. By using the basic rules of probability, the validity of both the optimization and the regression steps are insured. This statistically significant model is then integrated and inverted. The resulting output represents a project schedule which relates the amount of money spent to the percentage of project completion.

Johnson, Jesse P.↗

MTK: An AI tool for model-based reasoning

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Office is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control, and trend analysis of the Space Station Thermal Control System (TCS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined here with examples from the thermal system to highlight the motivating factors behind them, followed by an overview of the capabilities of MTK, which was developed to address these issues in a generic fashion.

Erickson, William K.↗

Building a Real-Time Predictive Flood Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the Howard County government in Maryland to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a prediction model capable of hindcasting the two severe flash flood events that devastated Ellicott City, and transitioned to an Long Short-Term Memory (LSTM) based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using the Nash-Sutcliffe Efficiency (NSE). The final product, called the Sequentially Trained Real-time EstimAted Model (STREAM), predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh (HRRR) model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate the OEM’s emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

Ryan Hammock↗

Building a Real-Time Flood Prediction Model for Improving Early Warning Systems in Ellicott City, Maryland

As flood events in the United States grow in frequency and intensity, the use of applied remote sensing analyses is increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP National Program partnered with the local government of Howard County, Maryland, to investigate the use of machine learning for advanced flood risk detection, and to test the feasibility of integrating this approach into the county’s flood early warning system. To strengthen the efforts of the Howard County Office of Emergency Management (OEM), the project developed a statistical model capable of hindcasting the two severe flash flood events that devastated Ellicott City and transitioned to a ‘Long Short-Term Memory’ based sequence-to-sequence deep learning model with 8-hour forecast capability. The team combined data inputs from public sources including river and precipitation gauges, NASA and NOAA Earth observations, and numerical weather model products using scripts written in the Google Colaboratory Python scripting environment. In addition to designing the deep learning architecture, the team trained and tested the model, and evaluated its performance using Nash-Sutcliffe Efficiency. The final product, the Sequentially Trained Real-time EstimAted Model (STREAM) predicts stage height for the Hudson Branch gauge in Ellicott City using data products available in near real-time, including the High-Resolution Rapid Refresh model’s accumulated precipitation forecasts supplemented by stream gauge data from the OEM and the U.S. Geological Survey. STREAM was incorporated into an online dashboard in a user-friendly interface capable of triggering the alarms that initiate emergency response protocols up to 8 hours in advance of a predicted severe flood event. The project demonstrated the potential for the integration of open data and Earth observations into a flood risk forecasting tool capable of informing near real-time decision making.

NASA DEVELOP↗

MTK: An AI tool for model-based reasoning

A 1988 goal for the Systems Autonomy Demonstration Project Office of the NASA Ames Research Center is to apply model-based representation and reasoning techniques in a knowledge-based system that will provide monitoring, fault diagnosis, control and trend analysis of the space station Thermal Management System (TMS). A number of issues raised during the development of the first prototype system inspired the design and construction of a model-based reasoning tool called MTK, which was used in the building of the second prototype. These issues are outlined, along with examples from the thermal system to highlight the motivating factors behind them. An overview of the capabilities of MTK is given.

Erickson, William K.↗

Microgravity Science and Applications: Program Tasks and Bibliography for Fiscal Year 1996

NASA's Microgravity Science and Applications Division (MSAD) sponsors a program that expands the use of space as a laboratory for the study of important physical, chemical, and biochemical processes. The primary objective of the program is to broaden the value and capabilities of human presence in space by exploiting the unique characteristics of the space environment for research. However, since flight opportunities are rare and flight research development is expensive, a vigorous ground-based research program, from which only the best experiments evolve, is critical to the continuing strength of the program. The microgravity environment affords unique characteristics that allow the investigation of phenomena and processes that are difficult or impossible to study an Earth. The ability to control gravitational effects such as buoyancy driven convection, sedimentation, and hydrostatic pressures make it possible to isolate phenomena and make measurements that have significantly greater accuracy than can be achieved in normal gravity. Space flight gives scientists the opportunity to study the fundamental states of physical matter-solids, liquids and gasses-and the forces that affect those states. Because the orbital environment allows the treatment of gravity as a variable, research in microgravity leads to a greater fundamental understanding of the influence of gravity on the world around us. With appropriate emphasis, the results of space experiments lead to both knowledge and technological advances that have direct applications on Earth. Microgravity research also provides the practical knowledge essential to the development of future space systems. The Office of Life and Microgravity Sciences and Applications (OLMSA) is responsible for planning and executing research stimulated by the Agency's broad scientific goals. OLMSA's Microgravity Science and Applications Division (MSAD) is responsible for guiding and focusing a comprehensive program, and currently manages its research and development tasks through five major scientific areas: biotechnology, combustion science, fluid physics, fundamental physics, and materials science. FY 1996 was an important year for MSAD. NASA continued to build a solid research community for the coming space station era. During FY 1996, the NASA Microgravity Research Program continued investigations selected from the 1994 combustion science, fluid physics, and materials science NRAS. MSAD also released a NASA Research Announcement in microgravity biotechnology, with more than 130 proposals received in response. Selection of research for funding is expected in early 1997. The principal investigators chosen from these NRAs will form the core of the MSAD research program at the beginning of the space station era. The third United States Microgravity Payload (USMP-3) and the Life and Microgravity Spacelab (LMS) missions yielded a wealth of microgravity data in FY 1996. The USMP-3 mission included a fluids facility and three solidification furnaces, each designed to examine a different type of crystal growth.

Source record↗

Complementary Roles of LEO and GEO IR Sounders in NWP Evaluated using an OSSE Framework

The United States is currently preparing for the next-generation weather satellite program. Building off the multi-decadal successes of the Low-Earth Orbit (LEO) infrared (IR) sounder program, NOAA and NASA are planning for the Geostationary eXtended Observations (GeoXO) Sounder (GXS) that will join international counterparts to form a global ring from geosynchronous orbit (GEO). To address questions about the complementarities and roles of these two platform types in the context of numerical weather prediction (NWP) and forecast accuracy, NASA’s Global Modeling and Assimilation Office (GMAO) Observing System Simulation Experiment (OSSE) framework was used to test their impact individually and in concert. Analyses, forecasts, and forecast sensitivity-based observations impact (FSOI) are examined. Overall, each has a role in forecast error reduction with the most beneficial impacts occurring when both LEO and GEO sounders are used together to address the needs of global skill and targeted regional weather phenomena.

Erica Mcgrath-Spangler↗

Prioritization of engineering support requests and advanced technology projects using decision support and industrial engineering models

The evaluation and prioritization of Engineering Support Requests (ESR's) is a particularly difficult task at the Kennedy Space Center (KSC) -- Shuttle Project Engineering Office. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant pieces of information concerning Safety, Supportability, O&M Cost Savings, Process Enhancement, Reliability, and Implementation. Various analytical and normative models developed over the past have helped decision makers at KSC utilize large volumes of information in the evaluation of ESR's. The purpose of this project is to build on the existing methodologies and develop a multiple criteria decision support system that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The model utilizes the Analytic Hierarchy Process (AHP), subjective probabilities, the entropy concept, and Maximize Agreement Heuristic (MAH) to enhance the decision maker's intuition in evaluating a set of ESR's.

Tavana, Madjid↗

Solutions Network Formulation Report. Using NASA Sensors to Perform Crop Type Assessment for Monitoring Insect Resistance in Corn

The EPA (U.S. Environmental Protection Agency) is tasked to monitor for insect pest resistance to transgenic crops. Several models have been developed to understand the resistance properties of insects. The Population Genetics Simulator model is used in the EPA PIRDSS (Pest Infestation and Resistance Decision Support System). The EPA Office of Pesticide Programs uses the DSS to help understand the potential for insect pest resistance development and the likelihood that insect pest resistance will negatively affect transgenic corn. Once the DSS identifies areas of concern, crews are deployed to collect insect pest samples, which are tested to identify whether they have developed resistance to the toxins in transgenic corn pesticides. In this candidate solution, VIIRS (Visible/Infrared Imager/Radiometer Suite) vegetation index products will be used to build hypertemporal layerstacks for crop type and phenology assessment. The current phenology attribute is determined by using the current time of year to index the expected growth stage of the crop. VIIRS might provide more accurate crop type assessment and also might give a better estimate on the crop growth stage.

Lewis, David↗